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--- |
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license: other |
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base_model: boun-tabi-LMG/TURNA |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: TURNA_emotion_single |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# TURNA_emotion_single |
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This model is a fine-tuned version of [boun-tabi-LMG/TURNA](https://huggingface.co/boun-tabi-LMG/TURNA) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5223 |
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- Accuracy: 0.908 |
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- Precision: 0.9133 |
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- Recall: 0.908 |
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- F1: 0.9065 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 0.4 | 50 | 1.5118 | 0.48 | 0.4815 | 0.48 | 0.3654 | |
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| No log | 0.8 | 100 | 0.9884 | 0.655 | 0.8127 | 0.655 | 0.5878 | |
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| 1.1187 | 1.2 | 150 | 1.2171 | 0.66 | 0.7893 | 0.66 | 0.6006 | |
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| 1.1187 | 1.6 | 200 | 1.2756 | 0.68 | 0.8250 | 0.68 | 0.6289 | |
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| 0.1624 | 2.0 | 250 | 1.3194 | 0.715 | 0.8334 | 0.715 | 0.6729 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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### Citation Information |
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``` |
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Uludoğan, G., Balal, Z. Y., Akkurt, F., Türker, M., Güngör, O., & Üsküdarlı, S. (2024). |
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Turna: A turkish encoder-decoder language model for enhanced understanding and generation. arXiv preprint arXiv:2401.14373. |
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``` |
